Demographic consequences of an extreme heat wave are mitigated by spatial heterogeneity in an annual monkeyflower

Abstract Heat waves are becoming more frequent and intense with climate change, but the demographic and evolutionary consequences of heat waves are rarely investigated in herbaceous plant species. We examine the consequences of a short but extreme heat wave in Oregon populations of the common yellow monkeyflower (Mimulus guttatus) by leveraging a common garden experiment planted with range‐wide populations and observational studies of 11 local populations. In the common garden, 89% of seedlings died during the heat wave including >96% of seedlings from geographically local populations. Some populations from hotter and drier environments had higher fitness, however, others from comparable environments performed poorly. Observational studies of local natural populations drastically differed in the consequences of the heat wave—one population was completely extirpated and nearly half had a >50% decrease in fitness. However, a few populations had greater fitness during the heat wave year. Differences in mortality corresponded to the impact of the heat wave on soil moisture—retention of soil moisture throughout the heat wave led to greater survivorship. Our results suggest that not all populations experience the same intensity or degree of mortality during extreme events and such heterogeneity could be important for genetic rescue or to facilitate the distribution of adaptive variants throughout the region.


| INTRODUC TI ON
Climate change is not only causing gradual increases in global mean temperatures but is also causing higher levels of variation in temperature and precipitation in specific areas across the world (Pachauri et al., 2014). This increase in variation suggests extreme climatic events, such as droughts, floods, and heat waves, will become more common and more severe in certain locations (Dai, 2013;Guerreiro et al., 2018;Pachauri et al., 2014;Scherrer et al., 2016).
While there is often time for species to disperse to areas with more optimal conditions during prolonged extreme events (Tingley et al., 2009), pulses of extreme climate conditions can be challenging for organisms with limited movement, potentially causing severe mortality with lasting demographic consequences or even extirpation (Jiménez et al., 2011;Ruthrof et al., 2018;Sumerford et al., 2000). Such extreme climatic events in natural populations are challenging to study because these events are rare by definition, occur unpredictably, are short-lived, and often require background information or data on a specific species collected before the event to address meaningful biological questions (Gutschick & BassiriRad, 2003).
Heat waves, defined as three or more consecutive days where the temperature is greater than the 90th percentile for a given location and time of year (Perkins & Alexander, 2013), have increased dramatically over the last century (Coumou et al., 2013;Della-Marta et al., 2007) and are predicted to further increase in frequency, duration, and intensity in the coming century (Coumou et al., 2013;Meehl & Tebaldi, 2004;Perkins-Kirkpatrick & Gibson, 2017). Such heat waves and associated water availability stress have been linked to mass mortality events in natural populations (Breshears et al., 2005;Matusick et al., 2018;Ruthrof et al., 2018) and substantial loss of yield or even complete crop failure in agricultural systems (Zampieri et al., 2017). However, there are relatively few studies of heat waves documented in natural populations, especially in herbaceous plant populations, that examine how these events impact immediate population fitness and long-term population dynamics (but see Sheth and Angert (2018), Thomson et al. (2018), Harrison and LaForgia (2019)). These data are critical for determining extirpation risks for populations and future evolutionary responses .
While native populations may struggle with extreme conditions caused by heat waves, geographically distant populations that have historically experienced hotter and/or drier conditions may be better adapted to such conditions. Indeed, experimental studies from crops and model systems including Oryza, Zea, and Arabidopsis indicate that there is substantial genetic variation in escape, avoidance, and tolerance to heat stress within species (Janni et al., 2020;Silva-Correia et al., 2014) and populations that experience heat stress more often are better adapted to it (Shah et al., 2011;VanWallendael et al., 2019). Additionally, adaptation lags, where geographically distant populations are better adapted than the native population to a site because of shifting climate, have been observed frequently in the context of variation in annual climates rather than in extreme short-term climatic events (Anderson & Wadgymar, 2020;Kooyers et al., 2019;Wilczek et al., 2014).
Alternatively, there are a number of reasons why populations from hotter and drier regions may not produce a fitness advantage over native populations during a heat wave. Historically, hotter and drier populations may not have evolved resistance mechanisms sufficient to withstand extreme and rapid heat waves. That is, optimal physiological performance at a higher temperature is not necessarily the same agent of selection as survival during short-term heat shock or performance within strongly fluctuating environments (Wang et al., 2020). Even if the population from the hotter/drier climate has a fitness advantage during an extreme event, it does not necessarily indicate that the associated phenotypes or allelic variation would increase in frequency within the native site. Distant populations may not be well adapted to other key abiotic and biotic selective agents within a native site (Bell, 2013). This maladaptation could manifest as a trade-off to heat resistance, where populations with high survivorship during the heat wave may also have lower fecundity at the novel site relative to the native population.
In cases where heat waves cause population declines or extirpation, natural levels of gene flow between geographically proximate populations may allow recolonization of populations that experience intense mortality or provide an influx of genetic variation (i.e., "genetic rescue") (Bell & Gonzalez, 2009;Fitzpatrick et al., 2016). This could be particularly important in environments with patchy habitats or in those that occur across steep environmental gradients, as geographically close populations may not experience equally extreme conditions as the focal population (Orr & Unckless, 2014). Assessing how nearby populations perform during an extreme event and the factors that cause heterogeneity in fitness may be as important as examining a focal population as these populations could provide an influx of individuals and genetic diversity to the focal population.
In this study, we examine how populations of a model species for ecological genetics, the common yellow monkeyflower (Mimulus guttatus; syn. Erythranthe guttata), perform during an extreme heat wave. Annual populations of M. guttatus occur throughout western North America in inland areas with ephemeral water supplies such as rock walls, seepy meadows, and flood plains (Wu et al., 2008). Annual plants germinate during spring rains or snow melt and senesce after producing seed during dry summers. The timing and length of the growing season vary dramatically across the range and there is considerable variation in the climates that different populations experience (Kooyers et al., 2015). Annual M. guttatus exhibits a wide range of phenotypic variation that allows for local adaptation to divergent environments (Friedman et al., 2015;Hall & Willis, 2006;Kooyers et al., 2019;Troth et al., 2018) and also has some of the highest levels of standing genetic variation across plant species Puzey et al., 2017;Twyford et al., 2020;Vallejo-Marín et al., 2021). These studies suggest that the genetic and phenotypic variation necessary to respond to selection due to an extreme event is likely present somewhere across this wide range.
Although M. guttatus is a common species unlikely to be threatened with extinction due to climate change, high-elevation populations in the Central Oregon Cascades are at risk. These populations have the shortest growing season of all known annual M. guttatus populations, lasting only from early June to mid-July (Kooyers et al., 2015). There is significant year-to-year variation in environmental conditions that can shift the growing season up to a month earlier (Kooyers et al., 2019;Troth et al., 2018). While populations maintain extremely high levels of polymorphism due to temporally fluctuating selection and fine-grain heterogeneity in water availability within populations, these populations are experiencing the extremes of the historical climatic normal (Mojica et al., 2012;Nelson et al., 2018;Troth et al., 2018) and adaptation lags to changing conditions have already been documented (Kooyers et al., 2019).
Here we investigate how M. guttatus populations from throughout the range and within local populations in the Central Oregon Cascades perform during an extreme, but short 8-day heat wave at the beginning of the growing season. Specifically, we use a common garden experiment to compare fitness from populations throughout the range of annual M. guttatus and we collect phenology and fitness data from nearby populations to better understand the metapopulation-wide consequences of an extreme heat wave. We use these data to address the following questions: (1) How do local populations perform relative to more geographically distant populations during an extreme event? (2) Do extreme weather events favor populations whose historical environment more closely matches the extreme event? (3) Are the consequences of heat waves homogenous across a metapopulation?, and (4) If not, is heterogeneity predictable by variation in environmental characteristics between sites?
We find that native populations performed poorly in our common garden, but some distant populations that historically encounter extreme heat more frequently have far higher fitness. Local populations also show considerable variation in responses to the heat wave with some populations avoiding negative fitness consequences entirely.

| Documenting an extreme event
During the second week of June 2019, we observed abnormally high temperatures and rapid dry-down following snowmelt in our long-term common garden and observation sites in the central Oregon Cascades. We took advantage of our existing infrastructure and ongoing experiments to examine the impact of this heat wave on M. guttatus populations. We quantified the magnitude of this heat wave by comparing climate in 2019 to historic averages.
We downloaded monthly averages of minimum, average, and maximum temperatures as well as average precipitation and precipitation as snow for each year from 1980 to 2019 from ClimateWNA (Wang et al., 2016)

| Common garden study
To examine how the heat wave influenced relative patterns of adaptation, we leveraged a common garden field experiment that contained outbred lines from 11 populations spanning much of the range of annual M. guttatus at the Browder Ridge site (Figure 1a).
Each outbred line was derived from seeds collected from 5 to 8 maternal families (Ave. 7.1). Latitude, longitude, and elevation of each site were taken at the time of collection and used to acquire climatic norms  for each population from ClimateWNA as well as haversine distances from each population to the Browder Ridge common garden. To generate outbred lines, maternal lines were grown for a single generation in a common garden greenhouse environment and crossed to another maternal line from the same population. Each maternal line acted as a pollen recipient in one cross and a pollen donor in a second cross.
We initiated the common garden by planting outbred line seeds in 2.25″ pots filled with Sunshine #1 (Sun Gro Horticulture) in unperforated 10″ × 20″ flats. We covered the flats with clear humidity domes, and cold-stratified the seeds in the dark at 4°C. After 7 days of stratification, we moved the flats to the University of Oregon greenhouse with ambient light and temperature conditions. Plants were misted and germination was recorded daily. Following 7 days in the greenhouse, we removed humidity domes and plants were bottom-watered as needed. After 14 days in the greenhouse, we randomized all pots into 12 blocks and transplanted seedlings directly into the field site. Microsite variation in water availability is high at this site with a natural population of M. guttatus spanning areas that dry out at different rates. We planted the blocks in locations that span this variation. Loss due to transplant shock has been minimal at this field site in past years (Colicchio, 2017;Kooyers et al., 2019;Troth et al., 2018). Timing matched the phenology of local populations. That is, all native plants were vegetative rosettes within a few weeks of germination.
We surveyed survival and flowering for each plant every other day. Survival was defined as having any living green tissue in leaves, stem or meristem (i.e., active chloroplast activity). No plant that was recorded as dead appeared later in the growing season as alive. To assess fecundity, we counted the number of flowers, collected all mature calyxes, and counted the seeds they contained. Below we report "inclusive number of flowers" as the total number of flowers where plants that did not survive or flower counted as zeros and "inclusive number of seeds" as the number of seeds produced where plants that did not produce seeds counted as zeros. We report both metrics because the number of flowers better includes fitness contributions through male fecundity while the number of seeds better represents female fecundity.

| Assessing differences in fitness between populations in the common garden
We determined how the native population performed relative to other populations throughout the M. guttatus range using linear mixed models and generalized linear mixed models (LMMs and GLMMs) implemented with the lmer() and glmer() functions in the lme4 v1.1-27.1 package (Bates et al., 2014) in R v4.1.1 (Institute for Statistic Computing). Separate univariate models were constructed for five different fitness components (survival to flowering, number of flowers, number of seeds, inclusive number of flowers, and inclusive number of seeds) as the response variable.
The number of seeds and the inclusive number of seeds were both log-transformed to improve the fit of the below models. Each model had population as a fixed factor and line as a random factor.
Additionally, variation among blocks in the garden was included as a random factor in both models. The GLMM assessing survival to flowering had a binomial error distribution with a logit link while LMMs were used for the number of flowers, number of seeds, inclusive number of flowers, and inclusive number of seeds (GLMMs using a Poisson family, and logit link had nearly identical results; Appendix 1: Table A1). Statistical significance of population was assessed via ANOVA using the Anova() function in the car v3.0-12 package (Fox et al., 2013). We compared the native population to all other populations by calculating line means for each variable and conducting Dunnett's tests with BR1 as the focal population.
Dunnett's tests were implemented using the DescTools v0.99.44 package. We note that our estimates of absolute fitness are likely elevated from natural populations as we transplanted seedlings to limit initial mortality.
We also investigated potential trade-offs between survival of the heat wave and fecundity by comparing whether lines that had a higher chance of surviving the heat wave were more likely to have higher fecundity. We constructed linear models to examine the as-

| Fitness-historical environment associations
We examined whether historic climatic differences among populations were associated with differences in fitness using a univariate GLMM approach with fitness variables as the response variables in independent models. All models included block, population, and line nested within the population as random variables and the environmental variable as a fixed factor. For each fitness variable, we ran separate GLMM for seven different environmental variables including geographic distance to the Browder Ridge common garden, mean annual temperature, annual heat moisture index, growing season start date, precipitation as snow, variance in spring maximum temperature, and variance in summer maximum temperature.
Variances were calculated from maximum spring and summer temperatures from 1960 to 2021 extracted from ClimateWNA. These factors were chosen because they have all been identified as potential agents of selection for M. guttatus in past studies (Kooyers et al., 2015(Kooyers et al., , 2019. Error distributions, links, and transformations are the same as described above. Statistical significance was determined by ANOVA as above.

| Impact of the heat wave on natural populations
We selected 11 natural populations distributed across an elevational gradient of ~600 m in a 10 km 2 region of Browder Ridge to examine variation in soil moisture, survivorship, and phenology across the 2019 growing season (Appendix 2: Figure A1). In each population, we surveyed two 0.25m 2 sampling grids (50 × 50 cm) every 7-14 days from snowmelt until population senescence. On each visit, we counted the number of vegetative, flowering, and senesced plants as well as measured volumetric water content with an SM150T soil moisture sensor (Dynamax). Grid locations were chosen within sites to encompass the natural variation within the site while only using areas with high concentrations of M. guttatus seedlings.
We examined how the number of individuals in each grid changed before, during, and after the heat wave to assess the mortality associated with the heat wave. To examine whether differences in soil moisture were driving differences in mortality between plots, we used an LMM to model whether the amount of mortality experienced in a grid during the heat wave was associated with the volumetric soil water content before the heat wave. Population was treated as a random factor in these models. Statistical significance of the fixed factors was assessed with lmerTest v3.1-3 using Satterthwaite's degrees of freedom method (Kuznetsova et al., 2017). We further examined variation in survivorship, phenology, and volumetric water content throughout the growing season by modeling mortality, flowering, and soil moisture through time and calculating summary statistics for each grid (see Appendix 3 for further methodology and models). Summary statistics included critical survivorship date (when 50% of plants still survived in a plot), peak flowering date, and date when VWC fell below 20% for the first time.

| Impacts of the heat wave on fecundity in natural populations
We examined the influence of the heat wave on fecundity using observational data collected at the end of the 2018 and 2019 growing seasons from 12 natural populations. Nine of these populations were the same ones as described above (Appendix 2: Figure A1). We Because the interaction between population and year was significant, we examined population means to determine the direction and magnitude of differences in each individual population between years. We also evaluated whether the relative differences in flower or seed production between 2018 and 2019 that we observed between populations was associated with the environmental characteristics of the populations. We modeled associations between the difference in seed production between years and each of six different environmental characteristics (elevation, mean annual temperature, mean coldest month temperature, the beginning of the frost-free period, precipitation as snow, and climate moisture deficit) using linear regressions implemented through the lm() function.
Differences in seed production between years were calculated from population averages.

Climate patterns in 2019 in the Central Oregon Cascade Mountain
Range closely resembled historic monthly normals for both temperature and precipitation ( Figure 1b). However, a severe heat wave occurred approximately 2 weeks following snow melt at the Browder Ridge field site. Data from the nearest NOAA weather station indicate max temperatures over an 8-day period were the hottest on record back to 1983 (Days 160-167; Figure 1c) and peaked at 30.4°C on Day 163 (June 12). The average maximum temperature during this stretch in 2019 exceeded the historic average maximum temperature by 8.5°C. In the Browder Ridge common garden, 89.0% of seedlings (438/492) died during the heat wave. There was a significant effect of block on survivorship (χ 2 = 141.1, p < .001). Survivorship in blocks ranged from 0% to 77.3% and only three blocks had >15% survivorship. Blocks where soil dried out later in the heat wave had higher survivorship suggesting that death was due to a combination of limited water availability and heat stress (A. Scharnagl, personal observation).

| Native populations have low relative fitness in common garden
There were significant differences in survivorship among populations planted in the common garden following the heat wave (χ 2 = 22.9, p = .01, Appendix 1: Table A1 Following the heat wave, there were no significant differences in fecundity among populations (number of flowers: F 8,42.6 = 1.8, p = .10; number of seeds: F 6,10.4 = 1.4, p = .30, Appendix 1: Table A1) and metrics of fitness that include both survival and fecundity closely resembled survival models, with significant variation among populations (Inclusive Number of Flowers: χ 2 = 47.0, p < .0001; Inclusive Number of Seeds: χ 2 = 40.1, p = .0002; Figure 2). Of the four populations that produced >1 seed/plant on average (i.e. an approximation of replacement level), the closest population to the BR common garden site was a lowelevation Oregon site (LPD) located 71.2 km away and the other three populations were from California. There was no evidence of a tradeoff between ability to survive the heat wave and fecundity following the heat wave. Lines that had higher survival during the drought produced more flowers than lines that had lower survival (r 2 = .29, p = .006; Appendix 5: Figure A2), but there was no relationship between viability and the number of seeds produced (r 2 = .07, p = .28, Appendix 5: Figure A2). Together these results suggest that local populations are less likely to survive and do not have a fecundity advantage over geographically distant populations following an early season heat wave.

| Populations from more arid areas do not necessarily perform better
Although there were clear differences among populations in both survivorship following the heat wave and inclusive number of flowers and seeds, these differences are not tightly associated with the historical environments of the populations (Figure 2d, Appendices 6 and 7). The only variable even marginally associated with any fitness metric was variation in spring maximum temperature with survival (χ 2 = 3.6, p = .06; Figure 2d). The three populations that best survived the heat wave were from notably warmer and more arid climates than Browder Ridge but there are other populations from similarly warm/arid climates that had very low survivorship (Appendix 6: Figure A3). Likewise, neither the inclusive number of flowers nor seeds was associated with any geographic or historical climate predictor (Appendix 7: Table A3).

| Widespread but variable mortality across a metapopulation
To better understand how this extreme heat wave could impact M.  Table A4). One population (HDM) had no individuals from either grid survive the heat wave. Other populations had extreme differences in survivorship between grids within a single population. For instance, one grid in BR1 had only 2% mortality during the heat wave while the other grid, located only ~1.5 m away, had 53.4% mortality. There was no relationship between elevation or other coarse environmental factors and survivorship in each grid during the heat wave (Appendix 9: Table A5). This lack of a pattern suggests small-scale microclimatic variation found within a population is most predictive of survivorship.

| Soil moisture is associated with survivorship
Since M. guttatus populations are characterized by having ephemeral supplies of water, we examined how soil moisture, survivorship, and phenology varied within and between natural populations as a potential key factor for understanding responses to the heat wave. Nearly all sampling grids dropped below 20% VWC during the heat wave, although several populations, particularly at higher elevations, returned above 20% later in the growing season (Appendix 10: Figure A4). There was a strong association between soil moisture before the heat wave and the mortality during the heat wave where grids with lower VWC before the heat wave had higher mortality (χ 2 = 9.1, p = .003; Figure 3b)-that is grids that dried down earlier had plants die earlier. Peak flowering occurred after critical survivorship dates in 76% of grids indicating that most plants died before flowering. There were substantial differences in peak flowering among populations with peak flowering occurring later in populations with later dry-down dates (Appendix 11: Figure A5). Combined, these data suggest that survival and phenology in these populations are strongly associated with variation in soil moisture rather than the actual heat stress associated with the heat wave.  Table A4). However, some populations had higher fecundity during the heat wave year. Two populations produced more flowers in 2019 than in 2018 (Figure 4; FIR and SEC) and four populations produced more seeds (Figure 4; FIR, SEC, OWC, SMG). Differences in fecundity between 2018 and 2019 were not associated with elevation, distance between populations, or any other environmental correlate that we examined (Appendix 12: Table A6). These data suggest that although the entire metapopulation experienced a heat wave, there was a large variation in how the heat wave impacted monkeyflower populations that is not predictable by the historic climate of a population.

| DISCUSS ION
The demographic consequences of extreme events, such as heat waves, are rarely explored, but such results are increasingly important in a changing climate. Our study provides a comprehensive examination of the heterogeneous consequences of a short but extreme heat wave for local and geographically distant pop-

ulations of M. guttatus. Specifically, we document that Central
Oregon populations experienced an extreme heat wave where high temperatures exceeded previous records. Plants from populations located near our common garden site were not well adapted to survive this event and those that did produced very few seeds.
However, several of the more distant populations were better able to survive and produce seeds. While these surviving populations did come from areas with greater variation in spring max temperature or historically lower annual heat-moisture indexes, other populations from similar areas did not have higher fitness.
The majority of natural populations near our common garden had lower fitness in the year of the heat wave relative to the previous year and one population had no individuals reproduce. However, some native populations did not experience the same degree of mortality and this variation was strongly associated with soil moisture levels. Together these results suggest that, even though some populations in the metapopulation could exhibit substantial decline or even extirpation, other nearby populations may not experience conditions as harsh and could act as source populations for highly-impacted populations. Below, we discuss the implications of our results and compare them to other studies of population dynamics following extreme events.

| Mortality within a heat wave
Our results indicate mortality during a heat wave can be extreme and may have long-lasting consequences for a population. While our heat wave was relatively short, we observed high mortality within our common garden experiment (~90% of plants died) as the heat wave occurred just as experimental plants were finishing establishing (transplanted 7 days prior to the start of heat wave).
While this could be considered mortality due to establishment shock, we suggest this is relatively unlikely given our observa- heat wave/drought in Western Australia averaged 26.0% mortality (SD 24.0%, range 0%-71%) . However, the majority of previous studies of heat waves may not be comparable as they have largely focused on longer events that are also associated with drought (Batllori et al., 2020) or examined longer-lived species (Mueller et al., 2005;Ruthrof et al., 2018). Basic data on the survival of herbaceous plants to extreme conditions in nature is a necessity for predicting future plant population dynamics but is currently in short supply.

| Historical aridity does not accurately predict heat wave survival
While mortality was high within both our common garden and natural populations, the fact that a minority of plants did survive and reproduce suggests there may be traits that facilitate survival. We expect populations from areas with historic climates that more closely match the extreme event to have higher fitness than native populations that rarely encounter such conditions -that is, an adaptation lag ( Table A2).
However, several populations that we assumed would do well under heat-stressed conditions (i.e. populations from southern California and the high elevations in the Sierra Nevada) also had very low fitness.
A key question is why some populations that are historically warmer and drier did not have improved survival of the heat wave. California populations used within this study (Kooyers et al., 2015Scharnagl et al., 2023). Notably, there are also large differences in magnitude and traits involved in plastic responses to dry-down conditions for the different populations used within this experiment, including differences in responses among California populations that could explain differential mortality (FitzPatrick et al., 2023). Future work should aim to link variation in trait variation and physiology to fitness consequences during extreme events.
One clear conclusion from our results is that the relative fitness patterns found in the heat wave-associated growing season (2019) do not match previous patterns found at the same location. We  Table A2). This difference is likely due to the nuanced changes in selection pressures between years. In 2014, abnormally high spring temperatures led to the growing season starting weeks earlier than normal, but precipitation was relatively normal throughout the year. In 2019, spring temperatures and snowfall were near average leading to a relatively normal growing season start date prior to the early season heat wave. Thus, in 2014, populations able to take advantage of the earlier-than-normal growing season were presumably favored while, in 2019, plants able to survive a high heat and low water climatic event as seedlings were likely favored. Temporal heterogeneity in selection pressures in these populations has been widely documented previously (Mojica et al., 2012;Troth et al., 2018), but this study demonstrates the fluctuations in the environment are substantial enough to enable populations with the lowest relative fitness in 1 year to have the highest relative fitness another year.
These results suggest predicting a population's tolerance to an extreme event is not as simple as examining historic environmental variation in the selective pressure under question.

| Metapopulations experience variation in the consequences of extreme events
Here we report that the heat wave had severe consequences on natural populations near the common garden site including complete mortality within one population and >50% mortality prior to flowering in several other populations (Figure 3a). Our results suggest that the most important factor for predicting mortality during the heat wave was the amount of nearby soil moisture present prior to the heat wave ( Figure 3b). This suggests that water rather than heat may have been the limiting factor during this heat wave. The consequences of this heat wave extended to differences in fecundity across most populations, with lower numbers of flowers and seeds produced per plant than in a more normal year (Figure 4). We hypothesize that the link between mortality and fecundity stems from either the delayed growth of seedlings following the heat wave or the selective mortality of smaller seedlings or rapidly reproducing plants during the heat wave. These hypotheses stem from observations of delayed phenology relative to other years within these populations (Appendix 10: Figure A4; N. Kooyers, personal observation).
However, we cannot rule out altered interactions with pollinators or herbivores (Walters et al., 2022).
While the amount of mortality seems like a relatively dire result, populations seldom exist in isolation and nearby populations may influence focal population dynamics both during and following an extreme event. Importantly, nearby populations may not experience the same severe selective conditions that a focal population receives and thus can act as a source for new migrants and replenish genetic variation following an extreme event through dispersal or gene flow (Fitzpatrick et al., 2016;Whiteley et al., 2015).
We suggest the heterogeneity we observe in mortality within and between populations mitigates the potential for complete extinction within the metapopulation due to a single extreme event and could allow for recolonization of extirpated sites. Gene flow between populations is likely high as there is very limited population structure between these populations . For populations that experience high mortality, an equally viable solution is the presence of a seed bank (Kalisz & McPeek, 1993;Walck et al., 2011). Seed banks in M. guttatus have long been hypothesized (Vickery, 1999), and our study provides additional evidence.

Recolonization has been frequently observed in other monkey
We followed the 'extirpated' population during the heat wave for the next 2 years (HDM). While there was no germination the following year (2020), there were a limited number of germinants in 2021 (30-40 individuals, S. Innes, personal observation). The remote nature of this population and the number of germinants suggests that these germinants came from the seed bank rather than from dispersal.
Our study highlights the difficulty in predicting species responses to extreme events. Detecting the risk of extirpation for other species requires determining how the particular event impacts the environment, how variation in the environment corresponds with variation in mortality, and accounting for reestablishment from the seed bank, dispersal, and gene flow.

| Long-term consequences of extreme heat waves
Long-term survival in a changing climate may require more than just the resurrection of populations from the seed bank or genetic rescue from other nearby populations. The heterogeneity in mortality from the heat wave across populations suggests our metapopulation is a ripe environment for the rapid evolution of heat and drought-resistance strategies (Grant et al., 2017). Such evolution to extreme events has been described in numerous other systems e.g. (Donihue et al., 2020;Franks et al., 2007;Grant & Grant, 1993) and can have long-term consequences for the populations (Grant & Grant, 1993). Given the high levels of genetic and phenotypic variation present in our monkeyflower populations Puzey et al., 2017) and a high degree of finegrain spatial and temporal heterogeneity in environmental factors that have promoted balancing selection (Troth et al., 2018), heat or drought-resistance related alleles may already be present within certain populations at low frequencies. These populations also exhibit a very limited population structure which suggests that gene flow is likely high . Thus, an adaptive variant that evolves in one population will likely spread to other nearby populations relatively quickly.
In conclusion, this study suggests that extreme heat waves can cause drastic declines in native populations, but such mortality may be ameliorated by micro-environmental variation, seed banks, and potential genetic rescue stemming from nearby populations. While this result is optimistic, we caution that survival of a single shortterm extreme event is not necessarily predictive when extreme events become normal. ing seeds. We thank Cheryl Friesen for her advice and assistance in obtaining permits. All research was permitted through the USFS within the Willamette National Forest. We thank the six anonymous reviewers who provided comments and improved this manuscript.

FU N D I N G I N FO R M ATI O N
Funding for this research came from the University of Louisiana, Lafayette and NSF grant DEB-2045643 to NJK.

CO N FLI C T O F I NTER E S T S TATEM ENT
The authors declare no competing interests that may have influenced this manuscript. Note: Inclusive number of flowers or seeds refer to the number of flowers or seeds, respectively, and include all plants that did not survive to flowering. Female fitness was log+1 transformed for all models.

A PPEN D I X 11
A PPEN D I X 12 F I G U R E A 5 Associations between dry-down dates and population phenology for Browder Ridge monkeyflower populations. Scatterplots depict associations between dry down date and either critical survival date (a) or flowering peak date (b). Dry down date was defined as the predicted day where volumetric water content drops below 0.2. Critical survival date was defined as the inflection point on a survival time series model. Peak flowering date was defined as the predicted day of peak flowering from fitted models.

TA B L E A 6
Associations between natural population fecundity in 2018 and 2019 with environmental characteristics.